Prominent Generative AI In Energy Market Trend for 2025: Generative AI For Real-Time Asset Performance Management In The Energy Sector

What industry-specific factors are fueling the growth of the generative ai in energy market?
The rise in solar electricity production is anticipated to fuel the expansion of generative AI in the energy sector. This type of electricity production transforms sunlight into electric power, either through photovoltaic (PV) panels or concentrated solar power (CSP) systems. The accelerating uptake of solar electricity can be attributed to both the falling prices of solar technology and a heightened public awareness of its eco-friendly aspects, such as its ability to reduce carbon emissions when compared to traditional fossil fuels. Integrating solar electricity generation with generative AI promises to increase the efficiency, reliability, and sustainability of power systems, aiding in the shift towards a greener and more resilient energy future. For example, in March 2023, the U.S. Energy Information Administration (EIA) and the U.S. Federal Statistical System forecasted that solar energy would be responsible for more than half of the new power capacity additions in the U.S. for the year. Worldwide, it's projected that renewable energy will grow from 29% of power generation in 2022 to 35% by 2025. Despite CO2 emissions from the global power sector peaking at 13.2 gigatons (Gt) in 2022, they are expected to plateau through 2025. In the U.S. in January 2023, utility-scale solar power represented 73.5 gigawatts (GW), or approximately 6% of the country's total power capacity. Wind power, meanwhile, accounted for 141.3 GW, or roughly 12% of the total. In addition, U.S. developers aim to expand wind capacity by 7.1 GW and add 8.6 GW of battery storage in the current year, effectively doubling the nation's battery storage capacity. Consequently, the growth of solar electricity production is spurring the development of generative AI in the energy industry.

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What Is the projected market size and growth rate for the generative ai in energy market?
In recent times, the market size of AI in the energy sector has seen an extraordinary expansion. It is projected to escalate from a size of $0.95 billion in 2024 to reach $1.21 billion in 2025, with a calculated annual growth rate (CAGR) of 26.7%. The unprecedented growth witnessed in the historical timeframe can be linked to the emergence of renewable energy mediums, forecasted demand, an increase in the storage systems for energy, demand response optimization, as well as the increasing emphasis on risk management and resilience.

The energy market related to generative AI is predicted to experience a skyrocketing growth trend in the coming years, with projections suggesting it will reach a size of $3.07 billion by 2029, reflecting a compound annual growth rate (CAGR) of 26.3%. This significant growth during the forecast period can be credited to factors such as enhanced precision, a rising demand for superior electricity distribution systems, an intensified concentration on customer engagement, a growing inclination towards using solar and wind energies, and an emerging prominence of asset management. Noteworthy developments anticipated in the forecast spell encompass real-time prognosis, flexible adaptation and maximization, improved predictive analytics, incorporation of advanced data origins, predictive maintenance and asset governance, and intelligent grid supervision.

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What are the emerging trends shaping the future of the generative ai in energy market?
Prominent businesses in the generative AI energy sector are striving to devise novel products like real-time asset performance management to streamline energy production, distribution, and consumption processes. Real-time asset performance management consists of the surveillance, examination, and enhancement of assets like machinery, equipment, or infrastructure, in real or near real-time. For example, in April 2024, Databricks Inc., an international data, analytics, and AI corporation based in the US, introduced a data intelligence platform devised for the energy sector. This integrated platform enables the utilization of AI on data and individuals in the energy sector. The platform addresses pivotal industry hindrances through real-time asset performance management, renewable energy prediction, and grid fine-tuning, empowering enterprises to improve energy infrastructure and cushion market instability. The Databricks data intelligence platform is structured on a lakehouse architectural model to provide an open, unified base for all data and governance. It is driven by a data intelligence engine that recognizes the distinctiveness of data.

What major market segments define the scope and growth of the generative ai in energy market?
The generative AI in energy market covered in this report is segmented -

1) By Component: Solutions, Services
2) By Application: Demand Forecasting, Renewable Energy Output Forecasting, Grid Management And Optimization, Energy Trading And Pricing, Customer Offerings, Energy Storage Optimization, Other Applications
3) By End User: Energy Transmission, Energy Generation, Energy Distribution, Utilities, Other End Users

Subsegments:
1) By Solutions: Energy Demand Forecasting, Predictive Maintenance Solutions, AI-Driven Energy Optimization Tools, Renewable Energy Management Solutions
2) By Services: Consulting Services, Implementation And Integration Services, Support And Maintenance Services, Training Services

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Which region dominates the generative ai in energy market?
North America was the largest region in the generative AI in energy market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the generative AI in energy market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

Which key market leaders are driving the generative ai in energy industry growth?
Major companies operating in the generative AI in energy market report are Google LLC; Microsoft Corporation; Engie SA; Enel Green Power S.p.A.; Huawei Technologies Co. Ltd; Amazon Web Services Inc; Siemens AG; General Electric Company; Intel Corporation; International Business Machines Corporation; Deloitte Touche Tohmatsu Limited; Cisco Systems Inc; Schneider Electric SE; Honeywell International Inc.; Flex Ltd; ABB Ltd; Duke Energy Corporation; Nvidia Corporation; Atos SE; Zen Robotics Ltd; Freshworks Inc.; C3 AI Inc; Databricks Inc; AppOrchid Inc; Verdigris Technologies; Ecube Labs Co. Ltd; Bidgely Inc

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What Is Covered In The Generative AI In Energy Global Market Report?

• Market Size Forecast: Examine the generative ai in energy market size across key regions, countries, product categories, and applications.
• Segmentation Insights: Identify and classify subsegments within the generative ai in energy market for a structured understanding.
• Key Players Overview: Analyze major players in the generative ai in energy market, including their market value, share, and competitive positioning.
• Growth Trends Exploration: Assess individual growth patterns and future opportunities in the generative ai in energy market.
• Segment Contributions: Evaluate how different segments drive overall growth in the generative ai in energy market.
• Growth Factors: Highlight key drivers and opportunities influencing the expansion of the generative ai in energy market.
• Industry Challenges: Identify potential risks and obstacles affecting the generative ai in energy market.
• Competitive Landscape: Review strategic developments in the generative ai in energy market, including expansions, agreements, and new product launches.

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